Swarm intelligence for iris recognition / Zaheera Zainal Abidin.

Author/creator Abidin, Zaheera Zainal, 1977-
Format Electronic
EditionFirst edition.
Publication InfoBoca Raton : CRC Press, Taylor and Francis Group, 2022.
Description1 online resource (ix, 135 pages)
Supplemental ContentFull text available from eBooks on EBSCOhost
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Uniform titleFurrow and crypt detection using modified ant colony optimization for iris recognition
Contents Human eye -- The first phase of iris recognition -- The second phase of iris recognition -- Swarm-inspired iris recognition.
Abstract "Iris recognition has been widely recognized as one of the most performing biometric system. The accuracy performance of iris recognition system is measured by FRR (False Reject Rate). FRR measures the genuine user who is incorrectly denied by the system due to the changes in iris features (such as aging and health condition) and external factors that affected the iris image to be high in noise rate. The external factors such as technical fault, occlusion, and source of lighting caused the image acquisition to produce distorted iris images problem hence incorrectly rejected by the biometric system. The current way of reducing FRR are wavelets and Gabor filters, cascaded classifiers, ordinal measure, multiple biometric modality and selection of unique iris features. Nonetheless, in the long duration of matching process, the previous methods unable to identify the user as a genuine since the iris structure itself produce a template changed due to aging. In facts, iris consists of unique features such as crypts, furrows, collarette, pigment blotches, freckles and pupil that are distinguishable among human. Previous research has been done in selecting the unique iris features however it shows low accuracy performance. Therefore, a new way of identifying and matching the iris template using nature-inspired algorithm is proposed in this book. As a conclusion, this book entitled as "Swarm Intelligence for Iris Recognition" brings an overview of iris recognition that naturally based on nature-inspired environment technology and provides benefits to the reader"-- Provided by publisher.
General note"A Science Publisher's book."
General noteOriginally presented as the author's thesis (doctoral)--Universiti Teknologi MARA, Shah Alam, 2016.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Source of descriptionDescription based on print version record and CIP data provided by publisher; resource not viewed.
Issued in other formPrint version: Swarm intelligence for iris recognition Boca Raton : CRC Press, Taylor & Francis Group, 2022. 9780367627478
Genre/formElectronic books.
LCCN 2021702134
ISBN9781000508215 ebook
ISBN(hardcover)
ISBN(paperback)

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